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@inproceedings{EK_Ocvirk2024,

title = {Primerjava metod za zaznavanje napadov ponovnega zajema},

author = {Krištof Ocvirk and Marko Brodarič and Peter Peer and Vitomir Struc and Borut Batagelj},

url = {https://lmi.fe.uni-lj.si/wp-content/uploads/2024/10/ocvirkprimerjava_metod.pdf},

year  = {2024},

date = {2024-09-26},

urldate = {2024-09-26},

booktitle = {Proceedings of ERK},

pages = {1-4},

address = {Portorož, Slovenia},

abstract = {The increasing prevalence of digital identity verification has amplified the demand for robust personal document authentication systems. To obscure traces of forgery, forgers often photograph the documents after reprinting or directly capture them from a screen display. This paper is a work report for the First Competition on Presentation Attack Detection on ID Cards, held at the International Joint Conference on Biometrics 2024 (IJCB PAD-ID Card 2024). The competition aims to explore the efficacy of deep neural networks in detecting recapture attacks. The Document Liveness Challenge Dataset (DLC-2021) was utilized to train models. Several models were adapted for this task, including ViT, Xception, TRes-Net, and EVA. Among these, the Xception model achieved the best performance, showing a significantly low error rate in both attack presentation classification error and bona fide presentation classification error.},

keywords = {attacks, biometrics, CNN, deep learning, identity cards, pad},

pubstate = {published},

tppubtype = {inproceedings}

}